This listing doesn't post a salary. Most similar roles pay
$144,350–$194,125.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As a Lead Infrastructure Engineer within the Corporate Sector – Chief Technology Office, you will join a high-performing team focused on infrastructure and performance excellence. You will manage workstreams across core domains including cloud networking, compute, storage, load balancing, DNS, and certificates while delivering end-to-end infrastructure changes for BI platforms across Windows, Linux, and AWS/SaaS environments. Your daily responsibilities involve automating delivery through Infrastructure as Code, troubleshooting complex cross-domain issues like SSO authentication and network connectivity, and implementing scalable solutions in collaboration with security and SRE teams. You will utilize enterprise-authorized AI capabilities to accelerate analysis and documentation while ensuring all outputs meet strict security and audit requirements. Required skills include proficiency in Python or other scripting languages, deep knowledge of cloud infrastructure, and experience managing large-scale BI tools like Qlik Sense, Tableau, or ThoughtSpot.
Develop and implement scalable solutions incorporating security controls like least privilege and encryption.
Create safe change plans including testing, phased rollouts, and backout procedures for large user bases.
Manage vendor relationships and coordinate incident responses for third-party SaaS platforms.
What we're looking for
Formal training or certification in infrastructure engineering concepts and 5+ years of applied experience.
Deep knowledge of core infrastructure areas including networking, databases, storage, deployment practices, automation, and performance assessment.
Demonstrated experience using enterprise-authorized AI capabilities to support infrastructure workflows with strong validation habits and data sensitivity awareness.
Ability to review and validate AI-assisted recommendations before implementation to ensure security and auditability.
Deep knowledge of cloud infrastructure across multiple public and private clouds including migration and vendor engagement.
Proficiency in scripting languages (e.g., Python) and Infrastructure as Code for automated, repeatable deployment patterns.
Hands-on experience operating Windows and Linux environments, including system services, patching, and performance troubleshooting.
Experience supporting enterprise BI platforms (Qlik Sense, Tableau, ThoughtSpot, or Sigma) and related integrations (preferred).